Map Data Compression Control for Memory Read Caching
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Solution Overview
Problem
Existing memory systems face challenges in efficiently caching map data due to the trade-off between compression ratio and parsing time, which affects read performance and hit rate, particularly in varying memory capacities.
Innovation Solution
A memory system that dynamically adjusts the compression ratio of map data based on available memory capacity, using a compressor to optimize the caching and parsing of map data, thereby managing overhead while maintaining a high hit rate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If map data is compressed at a high compression ratio to increase cache capacity, then the memory capacity utilization is improved, but the parsing time increases and read performance deteriorates
Solution Approach 1:
The patent applies dynamics by making the compression ratio adjustable rather than fixed. The controller dynamically selects different compression ratios based on the available memory capacity, allowing the system to adapt between cache capacity and parsing time requirements. When memory capacity is sufficient, a lower compression ratio is used to reduce parsing time; when memory capacity is limited, a higher compression ratio is used to maximize cache capacity utilization.
Solution Approach 2:
The patent changes the parameter of compression ratio based on memory capacity conditions. By varying this parameter, the system optimizes the balance between storing more map data in cache (higher compression ratio) and maintaining fast parsing performance (lower compression ratio). The controller monitors memory capacity and adjusts the compression ratio parameter accordingly to resolve the contradiction.
2Speed
If map data is compressed at a low compression ratio to reduce parsing time, then the read performance is improved, but the cache capacity is reduced and hit rate decreases
Solution Approach 1:
The system dynamically adjusts the compression ratio based on real-time memory capacity conditions. When memory capacity is sufficient, the system uses a lower compression ratio to prioritize fast parsing and read performance. When memory capacity is constrained, it switches to a higher compression ratio to maximize the amount of map data that can be cached, thereby maintaining hit rate.
Solution Approach 2:
The compression ratio parameter is changed according to memory capacity availability. The controller monitors the memory state and selects appropriate compression ratios from a set of predefined ratios, enabling the system to optimize between read performance (faster parsing with lower compression) and cache capacity (more data stored with higher compression).
3Reliability
If the memory capacity is increased to store more map data, then the cache hit rate is improved, but the system cost and complexity increase
Solution Approach 1:
Instead of increasing memory hardware capacity, the system changes the software parameter of compression ratio to optimize cache utilization. By using higher compression ratios when memory capacity is limited, the system can store more map data entries in the same physical memory space, thereby improving hit rate without adding hardware complexity.
4Quantity of substance
If the compression ratio is increased to maximize cache utilization, then the cache capacity is improved, but the overhead for compression and parsing increases
Solution Approach 1:
The system adjusts the compression ratio parameter based on memory capacity conditions rather than using a consistently high compression ratio. This allows the system to achieve good cache capacity utilization only when necessary (when memory is constrained), reducing the overall compression and parsing overhead while still maximizing cache effectiveness when needed.
Data Source
AI summary
An operating method of a memory system may include: searching for, in a memory, target map data corresponding to the read request; loading the target map data from a memory device when the target map data are not searched; compressing the loaded target map data using a predetermined compression ratio depending on an available capacity of the memory; caching the compressed target map data in the memory; parsing the compressed target map data; reading target user data corresponding to the read request from the memory device based on the parsed target map data; and outputting the read target user data.